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1. Alcohol and economic development: Observations on the kingdom of Bhutan.

Author

Kypri K, Dorji G, and Dalton C

Subjects
Adolescent, Adult, Aged, Alcohol Drinking legislation & jurisprudence, Alcoholic Beverages economics, Bhutan epidemiology, Driving Under the Influence legislation & jurisprudence, Driving Under the Influence prevention & control, Economic Development legislation & jurisprudence, Female, Health Policy legislation & jurisprudence, Health Surveys trends, Humans, Male, Middle Aged, Socioeconomic Factors, Young Adult, Alcohol Drinking economics, Alcohol Drinking trends, Driving Under the Influence trends, Economic Development trends, Health Policy trends
Abstract

Bhutan is a small country undergoing rapid social change arising from income growth, urbanisation and Western cultural influence. Markers of poverty, namely infectious disease and infant mortality, have improved dramatically. The attention of health authorities is now focused on the non-communicable disease and injury burdens, to which alcohol consumption is a major contributor. The paper draws on official data to characterise the consumption of alcohol and related harm, and the nature of the alcohol market, with commentary on crucial aspects of availability policies and drink-driving regulation that need reform. Kypri K, Dorji G, Dalton C. Alcohol and economic development: Observations on the kingdom of Bhutan. Drug Alcohol Rev 2017;36:333ȃ336.]., (© 2016 Australasian Professional Society on Alcohol and other Drugs.)

Published
2017
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2. Economic drivers and specialization patterns in the spatial distribution of Framework Programme's participation

Author

Dotti, Nicola Francesco, Spithoven, André, Doctoraatsbegeleiding, Dynamics in Innovation, Research and Higher Education, Onderzoekscoördinatie, and UCL - SSH/SPLE - Institut de sciences politiques Louvain-Europe

Subjects
specialization and diversification, spatial distribution, Geography, Planning and Development, Spatial distribution, Economie régionale et spaciale, Environmental Science (miscellaneous), Framework Programmes, economic development
Abstract

While R&D activities are known for being unevenly distributed across space, how EU policy contributed to their regional dynamics is less explored. Since the 1980s, the EU Framework Programmes (FP) have promoted and supported transnational R&D projects through open and highly competitive calls for funding driven by ‘scientific excellence’ regardless of location. This paper aims to show the drivers of this spatial distribution and evolution of FP participations, arguing that this depends on cumulative effects of regional economic development and growth, while scientific specialization rarely is the best strategy to improve regional competitiveness in terms of FP participations., SCOPUS: ar.j, info:eu-repo/semantics/published

Published
2018

3. Tourism demand forecasting with neural network models : Different ways of treating information

Author

Claveria, Oscar, Monte Moreno, Enrique|||0000-0002-4907-0494, Torra Porras, Salvador, Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla, and Universitat de Barcelona

Subjects
Artificial intelligence, Informàtica::Intel·ligència artificial::Aprenentatge automàtic [Àrees temàtiques de la UPC], Artificial neural networks, Radial basis function, Previsió econòmica, Economic development, Economic forecasting, Intel·ligència artificial, Computer Science::Neural and Evolutionary Computation, Multi-layer perceptron, Elman networks, Enginyeria de la telecomunicació [Àrees temàtiques de la UPC], Tourism, Neural networks (Computer science), Tourism demand, Desenvolupament econòmic, Informàtica [Àrees temàtiques de la UPC], Turisme, Xarxes neuronals (Informàtica), Informàtica::Intel·ligència artificial [Àrees temàtiques de la UPC], Perceptrons, Forecasting
Abstract

This paper aims to compare the performance of three different artificial neural network techniques for tourist demand forecasting: a multi-layer perceptron, a radial basis function and an Elman network. We find that multi-layer perceptron and radial basis function models outperform Elman networks. We repeated the experiment assuming different topologies regarding the number of lags used for concatenation so as to evaluate the effect of the memory on the forecasting results. We find that for higher memories, the forecasting performance obtained for longer horizons improves, suggesting the importance of increasing the dimensionality for long-term forecasting.

Published
2014